Perfusion Weighted Imaging in MRI - Admission/Application Essay Example

? Perfusion-Weighted Imaging in MRI Table of Contents I. Introduction 3 II. Exogenous Tracers 3 III. Endogenous Tracers 9 IV. Clinical Applications 13 References 17 I. Introduction This paper explores the use of endogenous and exogenous tracers in perfusion-weighted magnetic resonance imaging, focusing on a comparison and contrast of the two tracers and answering the question with regard to how the final information on perfusion is procured. The paper also goes into a discussion on the value that perfusion information has in clinical settings. Perfusion weighted magnetic resonance imaging or PWI makes use of energies from radio frequencies, computing technologies, and magnetic fields generate cross-section brain images that have high levels of detail. Aside from strokes, perfusion-weighted imaging are useful in the diagnosis of tumors of the brain and the pituitary gland, multiple sclerosis, disease of the pituitary system, and abnormalities of the cerebellum and of the brain stem. Two kinds of perfusion-weighted imaging make use of either endogenous or exogenous tracers, and in both kinds the result is the accurate determination of mean transit times or MTT, blood flow, blood volume and other quantitative haemodynamic characteristics (Stony Brook Medicine 2013; Neumann-Haefelin et al. 1999; Huisman and Sorensen 2004; Petrella and Provenzale 2000; Bochar 2001; Cutrer et al. 2004; Luypaert et al. 2001). II. Exogenous Tracers Endogenous and exogenous tracers refer to whether substances that are native to the human body or non-native to the human body respectively, and are both in use in perfusion-weighted imaging to determine the quantities tied to the hemodynamics of the sample being investigated. These quantities relate to the flow of blood, the volume of blood, and the time of transit of blood through the tracking of the tracer substance as it passes through the sample tissue. This latter time is also known as the mean transit time (Module 4: Perfusion Imaging 2013; Luypaert et al. 2001). In perfusion-weighted imaging in general, the tracer used is the agent that sensitizes the way blood microcirculates through a tissue or an organ’s network of capillaries and which also sensitizes the images formed with perfusion-weighted images themselves. The image intensity morphs as the tracer goes through the tissue capillary bed, so that the changes in intensity can be utilized for the determination for the metrics for blood that have been described above. The use of exogenous tracers allow for a comprehensive determination of the numerical numbers associated with the blood dynamics. This includes mean transit time, volume of blood, and flow of blood. In strokes, lesions translate to reduced volume and flow, while increasing mean transit times for the affected tissues in comparison to healthy, unaffected tissues. The image below typifies the three kinds of images that can be had from perfusion-weighted image protocols (Module 5: Applications of Perfusion and Diffusion 2013; Bochar 2001): Image source: Module 5 2013 In the images above, image (a) is for mean transit time, image (b) is for cerebral flow of blood, and image (c) is cerebral volume of blood. In all three images, it is noted that the right side of the brain exhibits abnormal perfusion (Module 5 2013, p. 4). Haemodynamic information is gathered in perfusion-weighted imaging making use of exogenous tracers via a reliance on inflow effects as well as susceptibility from a magnetic point of view. The exogenous tracer is sometimes introduced into the venous system via an injection, such as in the case of the exogenous tracer gadolinium. For this purposes, to be exact, the form that gadolinium takes is gadolinium dieethyltriamine pentaacetate or the Gd-DTPA compound. As the perfusion of the exogenous tracer occurs through the subject tissues, the signal undergoes a transient loss, which can then be subjected to MRI following. The paramagnetic characteristics of this exogenous tracer translate to differences in how susceptible different capillaries are depending on whether the capillaries contain the exogenous tracer gadolinium or not. The consequence of this is that around the vessel walls powerful gradient fields are detected, that in turn translate to the direct dephasing of signals in images from gradient echo, and a dephasing that is mediated by diffusion in images from spin echo. In gadolinium, in particular, where the gadolinium passes through the tissues, there is a loss or a weakening in the detected signal. The signal strength returns to its normal levels once the gadolinium has gone through the tissues concerned. Taking a step back, the following schematic describes the use of the exogenous tracer gadolinium as a representative tracer and mapping the methodology for perfusion-weighted imaging making use of that exogenous tracer (Module 4 2013, pp. 3-4; Petrella and Provenzale 2000; Roberts et al. 1994, pp. 33-37): Image source: Module 4 2013, p. 3 The equation below meanwhile summarizes the loss of signal due to the passage of the exogenous tracer gadolinium through the subject tissue capillaries (Module 4 2013, p. 4): In the equation above, So denotes the signal levels where there is no exogenous tracer present. The degree of the signal loss is a function of the multiplier to the right of that, which is composed of a difference factor for the relaxation rates tied to the gadolinium, one, and two the sequence echo time TE. This latter factor is responsible for the control of the T2 images weightings. Delta R2 is proportional to the tracer concentration (Module 4 2013, p. 4). There are differences on the other hand with the use of gadolinium as an exogenous tracer when it is paired either with T1 or T2 contrasts, with T1 contrasts mostly utilized for perfusion studies for the heart, as in the case of T1 contrasts for MR angiography, and T2 contrasts being done for perfusion contrasts for the brain (Module 4 2013, p. 5). The traversing of the exogenous tracer through the concerned organ or tissue can be tracked with the use of appropriate sequences, either gradient echo or spin, with the most prevalently used being the sequence called EPI, which is useful for the rapidity of its mode of acquiring images for perfusion imaging. This rapidity is needed in order to take full advantage of the characteristics of the perfusion of the tracer, which requires fast sequences for capturing images to be able to take full advantage of those tracer characteristics in aid of producing images of good detail. The image below shows that EPI beat fast spin echo in terms of getting through a greater portion of the brain in imaging for short time durations, for the same amount of time spent doing the imaging (Module 4 2013, pp. 5-6; Petrella and Provenzale 2000; Roberts et al. 1994): Image source: Module 4 2013, p. 4 Meanwhile, tracer kinetics-based analyses are necessary in order to understand and get accurate measurements of the key measures of mean transit time, and blood flow and blood flow volume. Among the assumptions in tracer kinetics is that blood flow is equal to tracer flow, and that the perfusion occurs at a constant rate and is not tracer-affected. Moreover, tracer kinetics assume that only the input is the sole source of the blood or the tracer, and that only the output is the blood and tracer sink. Moreover, in tracer kinetics, what is of interest is the amount of the tracer that persists in the organ or tissue through time, or what is called the residual amount of the tracer. The residual function is described below, with the correlation to the haemodynamic properties of the target (Module 4 2013, p. 8; Neumann-Haefelin et al. 1999; Luypaert et al. 2001): Image Source: Module 4 2013, p. 8 In the diagram above, the area is the mean transit time or MTT. The relevant equation for this is that the MTT is just the integral, or the area under the curve, of the residue function (Module 4 2013, p. 9): On the other hand, the concentration of the exogenous tracer as a function of time is given by the following equation (Module 4 2013, p. 9): The tracer concentration is just the probabilistic sum of all the tracer volume that entered the system during a period of time (Module 4 2013, p. 9). III. Endogenous Tracers Endogenous tracers are tracers that are present in the human body naturally and in place of external tracers are used for the purposes of generating perfusion-weighted images. Water that is naturally present in the human blood is a natural endogenous tracer. The protons of the water molecules are subjected to inversion before the water molecules are perfused through the tissue or organ portion of interest. Having gone through an inversion, the water molecules will be magnetized in a way that is different from non-inverted blood. There will be two images to compare, one with the inverted blood and one with the normal blood. The comparison yields the isolation of the signals for blood that is coming into the tissue slice or organ slice of interest/. There is a proportionality between the differences in the signals and the volume of blood that goes through the tissue portion of interest, and in this sense the haemodynamic characteristics are measured and quantified. Such methods yield what is known as the perfusion method called arterial spin labeling or ASL, or arterial spin tagging or AST. The application of the inversion force is what constitutes the change in spin, which is then labeled or tagged and used as the basis for undertaking numerical measurements of blood flow, volume, and mean transit time like in the previous methods that make use of exogenous tracers in place of water in blood. The figure below represents the endogenous tracer-based perfusion imaging process in schematic form (Module 4 2013, pp. 10-12; Neumann-Haefelin et al. 1999; Roberts et al. 1994, pp. 33-37): Image Source: Module 4 2013, p. 12 There is an analog to ASL in PET or O positron emission tomography, in the area of the sufficiently long time for signal decay in ASL that lends itself to the signals having enough time for the proper capture and processing of the images. For both imaging methods the decay rate of the tracer is established, and so is reliably used in computing for the perfusion figures. MRI perfusion that makes use of ASL and PET imaging samples are placed side by side for comparison in the image below (Module 4 2013, p. 13): Image source Module 4 2013, p. 12 Meanwhile, there are two additional characteristics of note for ASL imaging. One is that the differences in intensities between “treated” or inverted molecules and ordinary molecules in blood are only very small, in the area of about two percent difference, so that there is the need to take into consideration the signal to noise ratios of the captured signals. They factor into the accuracy of the images. Moreover, the images are subject to distortion from sample movement owing to the very small differences in the change in signal from ASL, so that there is a need to make sure that the capture process is sufficiently fast. For this reason ASL imaging techniques make use of EPI or fast spin echo, as has been discussed in perfusion imaging making use of exogenous tracers such as gadolinium (Module 4 2013, p. 13; Luypaert et al. 2001). Meanwhile, magnetization effects effectively dim the successful imaging of the brain for instance for techniques that make use of excitation methods for water molecules in the blood, which is the case for ASL imaging. This being so, there is a need to develop an intervening mechanism in order to compensate for the signal and image clarity loss. This process of excitation that leads to signal blurring is known as off-resonance excitation, which leads to the transfer of magnetization. The intervention involves the excitation or inversion of blood molecules in a position that follows from the portion of interest, along the blood flow. This state of affairs is illustrated in the graphic below (Module 4 2013, p. 14): Image Source: Module 4 2013, p. 14 Two methods for ASL that have been discussed are CASL, for continuous ASL, and Pulsed ASL In CASL, there is an almost continuous inversion of incoming flow or saturation of inversion of the water molecules in the slice of interest. The blood is inverted as it goes into the sample of focus so to speak, via what is known as a frequency sweep, effecting the inversion. There is the danger that this process can increase the levels of SAR in the subject to levels that may be dangerous, so that it is not used in conjunction with high levels of magnetization when there is a need to up the SAR levels. The continuity of the inversion meanwhile results in the steady state being assigned to the magnetized or inverted state. The image below details a schematic of this process (Module 4 2013, p. 16; Roberts et al. 1994): Image source: Module 4 2013, p. 16 In pulsed ASL, there is a pulsed rf signal that effects the magnetization of large volumes of water incoming into the tissue of interest (Module 4 2013, p. 17). The basic equation for explaining the way inverting the magnetization of water molecules in blood results in the successful perfusion-weighted imaging of human tissues and organs is given below, where delta M is the difference in the magnetization attributed to labeling of the blood flow (Module 4 2013, p. 18): Equation source: Module 4 2013, p. 18 IV. Clinical Applications Perfusion-weighted imaging or PWI has applications in stroke pathology and diagnosis, as discussed in the literature (Chalela et al. 2000). Other than that, PWI is also shown to have clinical applications in imaging tumors for diagnosis as well as for characterization; the differentiating tumors and cysts; determining how viable heart tissue is; imaging with the use of temperature gradients; applying perfusion techniques for neurological uses in migraines, dementia, and for functional imaging purposes. The table below details such clinical applications for perfusion imaging on the right side of the table (Module 6 2013, p. 5; Bochar 2001): Table source: Module 6 2013, p. 5). Perfusion imaging for instance has found wide application for imaging all kinds of cancer throughout the body, as for instance in differentiating between tumors and cysts. The picture below demonstrates the power of perfusion imaging to differentiate and identify cysts from tumors with great accuracy (Module 6 2013, p. 9; Roberts et al. 1994, pp. 33-37): Image source: Module 6 2013, p. 9 In the images above, there is a cyst in the upper right pole of the kidney and none at the lower pole. This reality is captured accurately and diagnosed with the use of perfusion imaging techniques (Module 6 2013, p. 9). Perfusion imaging also works in differentiating between tumor reoccurrences on the one hand and tissue death or necrosis. The perfusion in tissues is of lower value in tissues that have been cast to death by radiation, or tissues that went into necrosis as a result of the radiation, and this lower value is differentiated with values for tumors that have reoccurred. In the image below, the use of exogenous tracers in a perfusion imaging technique made it possible to image and diagnose the progression of brain tumor growth (Module 6 2013, p. 11; Huisman and Sorensen 2004): Image source: Module 6 2013, p. 11 Similarly, perfusion imaging with exogenous tracers is useful in grading tumors, because perfusion varies according to the grade of the tumors in different cancers. In the image below, the perfusion images were able to help in determining that the cancer tumor is of grade 3-4 (Module 6 2013, p. 13; Roberts et al. 1994; Luypaert et al. 2001; Niendorf 2003): Image source: Module 6 2013, p. 13 References Bochar, S. 2001. Diffusion and perfusion-weighted magnetic resonance imaging of acute ischemic stroke. Applied Radiology Journals 30 (4). http://www.appliedradiology.com/Issues/2001/04/Supplements/Diffusion-and-perfusion-weighted-magnetic-resonance-imaging-of-acute-ischemic-stroke.aspx [Accessed 12 October 2013] Chalela, Julio et al. 2000. Magnetic Resonance Perfusion in Acute Ischemic Stroke Using Continuous Arterial Spin Labeling. Stroke 31. http://stroke.ahajournals.org/content/31/3/680.long [Accessed 12 October 2013] Cutrer, F. Michael et al. 2004. Perfusion-weighted imaging defects during spontaneous migrainous aura. Annals of Neurology 43 (1). http://onlinelibrary.wiley.com/doi/10.1002/ana.410430108/abstract?deniedAccessCustomisedMessage=&userIsAuthenticated=false [Accessed 12 October 2013] Huisman, TA and Sorensen, AG 2004. Perfusion-weighted magnetic resonance imaging of the brain: techniques and application in children. Eur Radiol 14(1). [Online] Available at: http://www.ncbi.nlm.nih.gov/pubmed/12827431 [Accessed 12 October 2013] Luypaert, R. et al. 2001. Diffusion and Perfusion MRI: basic physics. European Journal of Radiology 38. [Online] Available at: http://folk.uib.no/nmaxt/levelset/luypaert_etal_diff_perf_2001.pdf [Accessed 12 October 2013] Module 4: Perfusion Imaging. 2013. Handouts/Notes. Module 5: Applications of Perfusion and Diffusion. 2013. Handouts/Notes. Module 6. Applications of Perfusion and Diffusion 2013. Handouts/Notes. Neumann-Haefelin, T. et al. 1999. Diffusion- and perfusion-weighted MRI. The DWI/PWI Mismatch Region in Acute Stroke. Stroke 30(8). [Online] Available at: http://www.ncbi.nlm.nih.gov/pubmed/10436106 [Accessed 12 October 2013] Niendorf, Eric. 2003. Magnetic resonance perfusion imaging and tumor angiogenesis. Applied Radiology Journals 32. http://www.appliedradiology.com/Issues/2003/06/Supplements/Magnetic-resonance-perfusion-imaging-and-tumor-angiogenesis.aspx [Accessed 12 October 2013] Petrella, J. and Provenzale, J 2000. MR Perfusion Imaging of the Brain. American Journal of Roentgenology 175(1). [Online] Available at: http://www.ajronline.org/doi/full/10.2214/ajr.175.1.1750207 [Accessed 12 October 2013] Roberts, David et al. 1994. Quantitative magnetic resonance imaging of human brain perfusion. Proc. Natl. Acad. Sci. USA 91. http://www.pnas.org/content/91/1/33.full.pdf [Accessed 12 October 2013] Stony Brook Medicine 2013. MRI (Perfusion/Diffusion Weighted). Stony Brook Neurosciences Institute. [Online] Available at: http://www.stonybrookneurosciences.org/MRI-Perfusion-Diffusion-Weighted.html [Accessed 12 October 2013] Read More